Skip to main content

Engagement and Satisfaction: Mixed-Method Analysis of Blended Learning in the Sciences

Canadian Journal of Science, Mathematics and Technology Education volume 21, pages 100–122 (2021)Cite this article

Abstract

Recent advancements in technology and increased globalization due to the internet have led to the development and popularization of asynchronous teaching formats. One of these is blended learning (BL), which combines online and physically in-person learning. While it is widely agreed that BL formats lead to measurable increases in student performance, little is understood about the relationship between student satisfaction and improved performance. We conducted an analysis of student and instructor feedback collected from surveys and interviews from four science courses converted from physically co-located to BL formats at a Canadian university. We specifically probed students’ experiences of BL, and student satisfaction in the blended format. We find that emotional engagement is a broadly applicable predictor of student satisfaction and success in BL courses. Specifically, we recommend instructors maintain personal connection with students, use collaborative active learning strategies, and emphasize alignment of learning activities with learning objectives. These may enhance the student experience and minimize challenges that have become characteristic of asynchronous teaching formats.

Résumé

Les récents progrès technologiques et l’accroissement de la mondialisation en raison d’internet ont conduit à l’avènement et à la diffusion des modèles pédagogiques asynchrones. Parmi ceux-ci, la formation par apprentissage hybride (AH) intègre aux méthodes traditionnelles d’enseignement en personne l’apprentissage en ligne. Bien qu’il soit généralement reconnu que les modèles AH entrainent une hausse mesurable du rendement des étudiants, on en sait très peu sur les raisons qui expliquent l’efficacité de la formation par apprentissage hybride et les relations qui existent entre le niveau de satisfaction des apprenants et l’amélioration de leur rendement. Nous avons analysé les commentaires provenant d’étudiants et d’enseignants d’une université canadienne dans quatre cours de sciences passés du mode d’enseignement en personne au modèle AH, recueillis à partir de sondages et d’entrevues. Plus précisément, nous avons sondé les expériences des étudiants en matière de formation AH et leur niveau de satisfaction par rapport au modèle hybride. Nous constatons que l’investissement sur le plan affectif constitue un indicateur significatif du niveau de satisfaction et de réussite des étudiants dans les cours en modes AH. Plus précisément, nous recommandons aux enseignants de cultiver un lien personnel avec les étudiants, d’utiliser des stratégies d’apprentissage actives et coopératives et de mettre l’accent sur l’alignement des activités et des objectifs d’apprentissage. Ces mesures peuvent rehausser l’expérience des étudiants et atténuer les défis normalement associés aux modèles pédagogiques asynchrones.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Data Availability

The datasets used and/or analysed during the current study may be available from the corresponding author on reasonable request as some data may be confidential. Additionally, participants did not consent to the storage of the datasets on a data repository or the release of individualized data.

Notes

  1. For all four courses, there were no differences in results between FIRST, LAST, LMG, and PRATT bootstrap measures.

References

  • Andrews, B. D. (2018). Delayed Enrollment and Student Involvement: Linkages to College Degree Attainment. The Journal of Higher Education, 89(3), 368–396.

    Article  Google Scholar 

  • Anderson, W. A., Banerjee, U., Drennan, C. L., Elgin, S. C., Epstein, I. R., Handelsman, J., Hatfull, G. F., Losick, R., O'Dowd, D. K., Olivera, B. M., Strobel, S. A., Walker, G. C., & Warner, I.M. (2011). Science education. Changing the culture of science education at research universities. Science 14, 331(6014), 152–153.

  • Association of Universities and Colleges of Canada on Trends in Education, Trends in Higher Education Volume 1 – Enrolment. (2011). Available from https://www.univcan.ca/wp-content/uploads/2015/11/trends-vol1-enrolment-june-2011.pdf

  • Bandura, A. (1997). Self-Efficacy: The Exercise of Control. New York: Freeman

    Google Scholar 

  • Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of Social and Clinical Psychology, 4(3), 359–373.

    Article  Google Scholar 

  • Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289.

    Article  Google Scholar 

  • Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M., & Abrami, P. C. (2014). A meta-analysis of blended learning and technology use in higher education: From the general to the applied. Journal of Computing in Higher Education, 26(1), 87–122.

    Article  Google Scholar 

  • Canadian Digital Learning Research Association. (2018). Tracking Online and Distance Education in Canadian Universities and Colleges. Retrieved from https://onlinelearningsurveycanada.ca/download/556/

  • Carless, D. (2013). In D. Boud and E. Molloy (Eds.), Feedback in Higher and Professional Education (pp. 90-103). Abingdon: Routledge.

  • Cole, M. & Wertsch, J. V. (1996) Beyond the Individual – social antinomy in discussions of Piaget and Vygotsky. Human Development, 39(5), 250–256.

  • Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.

  • Cross, K. P. (1981). Adults as Learners. Increasing Participation and Facilitating Learning. San Francisco, California: Jossey-Bass, Inc.

    Google Scholar 

  • Dale, M. (2010). Trends in the Age Composition of College and University Students and Graduates. Retrieved from: https://www150.statcan.gc.ca/n1/pub/81-004-x/2010005/article/11386-eng.htm#a

  • Duarte, P. O., Raposo, M. B. and Alves, H. B. (2012), Using a Satisfaction Index to compare students’ satisfaction during and after higher education service consumption. Tertiary Education and Management, 18 (1), 17–40.

    Article  Google Scholar 

  • El-Mowafy, A., Kuhn, M., & Snow, T. (2013). Blended learning in higher education: Current and future challenges in surveying education. Issues in Educational Research, 23(2), 132–150.

    Google Scholar 

  • Freeman S., O’Connor E., & Parks J., Cunningham M., Hurley D., Haak D., Dirks C., & Wenderoth M.P. (2007). Prescribed active learning increases performance in introductory Biology. CBE Life Science Education, 6, 132–139.

    Article  Google Scholar 

  • Freeman S., Eddy S., McDonough M., Smith M.K., Okoroafor N., Jordt H., & Wenderoth M.P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings in National Academic Science USA, 111, 8410–8415.

    Article  Google Scholar 

  • Fredricks, J. A., Blumenfeld, & Paris, A. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research 74(1) pp. 59–109

    Article  Google Scholar 

  • Fredricks, J. A., Blumenfeld, P., Friedel, J., & Paris, A. (2005). School engagement. In What do children need to flourish? Conceptualizing and measuring indicators of positive development. (pp. 305–321). Springer, Boston, MA.

  • Garrison, D.R., Anderson, T., & Archer, W. (2010). The first decade of the community of inquiry framework: A retrospective. Internet and Higher Education, 13, 5-9.

    Article  Google Scholar 

  • Goldrick-Rab, S., & Han, S. W. (2011). Accounting for socioeconomic differences in delaying the transition to college. The Review of Higher Education, 34(3), 423–445.

    Article  Google Scholar 

  • Hameed, S., Badii, A., & Cullen, A. J. (2008). Effective e-learning integration with traditional learning in a blended learning environment. In European and Mediterranean Conference on Information Systems (pp. 25–26).

  • Handelsman, J., Ebert-May, D., Beichner, R., Bruns, P., Chang A., DeHaan R., Gentile J., Lauffer S., Stewart J., Tilghman, S.M., Wood, W.B. (2004). Education. Scientific teaching. Science, 23, 304(5670), 521–2.

  • Hara, N., & Kling, R. (2001). Student distress in web-based distance education. Educause Quarterly, 24(3), 68–69.

  • Hassana, R. A., & Woodcock, A. (2014). Blended learning: Issues and concerns. Coventry School of Art and Design, 1(1), 1–8

    Google Scholar 

  • Jacobs, J. A., & King, R. B. (2002). Age and college completion: A life-history analysis of women aged 15–44. Sociology of Education, 211–230.

  • Kuh, G. D., Cruce, T. M., Shoup, R., Kinzie, J., & Gonyea, R. M. (2008). Unmasking the effects of student engagement on first-year college grades and persistence. The Journal of Higher Education, 79(5), 540–563.

    Article  Google Scholar 

  • Landis J.R., & Koch, G.G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1),159–74.

  • Lee, Y., & Choi, J. (2011). A review of online course dropout research: Implications for practice and future research. Educational Technology Research and Development, 59(5), 593–618.

  • Lipman, M. (1991). Thinking in education. Cambridge, UK: Cambridge University Press.

    Google Scholar 

  • Lo, C. C. (2010). How student satisfaction factors affect perceived learning.

  • López-Pérez, M. V., Pérez-López, M. C., & Rodríguez-Ariza, L. (2011). Blended learning in higher education: Students’ perceptions and their relation to outcomes. Computers & Education, 56(3), 818–826.

    Article  Google Scholar 

  • Maki, R. H., Maki, W. S., Patterson, M., & Whittaker, P. D. (2000). Evaluation of a Web-based introductory psychology course: I. Learning and satisfaction in on-line versus lecture courses. Behavior Research Methods, Instruments, & Computers, 32(2), 230–239.

  • Melser, D. (2004). The act of thinking. Cambridge: MIT Press.

    Book  Google Scholar 

  • Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies.

  • Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115(3), 1–47.

    Google Scholar 

  • Minick, N. (1987). Implications of Vygotsky's theories for dynamic assessment.

  • Nanclares, N. H., & Rodríguez, M. P. (2016). Students' Satisfaction with a Blended Instructional Design: The Potential of" Flipped Classroom" in Higher Education. Journal of Interactive Media in Education, (1).

  • National Research Council. (2012). Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering. Washington, DC: The National Academies Press. https://doi.org/10.17226/13362

  • National Student Clearinghouse: Research Center on College Completion, Completing College: A National View of Student Attainment Rates – Fall, (2010). Cohort, available from https://nscresearchcenter.org/wp-content/uploads/SignatureReport12.pdf

  • Nortvig, A., Petersen, A. K., & Balle, S. H. (2018). A literature review of the factors influencing e-learning and blended learning in relation to learning outcome, student satisfaction and engagement. Electronic Journal Of E-Learning, 16(1) 46–55.

    Google Scholar 

  • Oliver, R. (1997). Satisfaction: A behavioral perspective on the consumer. Irwin: McGraw-Hill.

    Google Scholar 

  • Ormrod, J.E. (2016). Human learning (7th ed.). London, UK: Pearson.

    Google Scholar 

  • Owston, R., York, D., & Murtha, S. (2013). Student perceptions and achievement in a university blended learning strategic initiative. The Internet and Higher Education, 18, 38–46.

    Article  Google Scholar 

  • Paechter, M., Maier, B., & Macher, D. (2010). Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computers & Education 54(1), 222–229.

  • Palincsar, A. S. (1998). Social constructivist perspectives on teaching and learning. Annual Review of Psychology, 49, 345–375. https://doi.org/10.1146/annurev.psych.49.1.345

  • Pike, G. R., Kuh, G. D., & Massa-McKinley, R. C. (2008). First-year students' employment, engagement, and academic achievement: Untangling the relationship between work and grades. Naspa Journal, 45(4), 560–582.

    Google Scholar 

  • Poon, J. (2012). Use of blended learning to enhance the student learning experience and engagement in property education. Property Management, 30(2), 129–156.

    Article  Google Scholar 

  • Reyes, M. R., Brackett, M. A., Rivers, S. E., White, M., & Salovey, P. (2012). Classroom emotional climate, student engagement, and academic achievement. Journal of Educational Psychology, 104(3), 700.

    Article  Google Scholar 

  • Roksa, J., & Velez, M. (2012). A late start: Delayed entry, life course transitions and bachelor's degree completion. Social Forces, 90(3), 769-794.

    Article  Google Scholar 

  • Shaienks, D.; Gluzynki, T.; Bayard, J. (2008). Postsecondary Education – Participation and Dropping Out: Differences Across University, College and Other Types of Postsecondary Institutions. Retrieved from: https://www150.statcan.gc.ca/n1/en/catalogue/81-595-M2008070

  • Sikora A., & Carroll, C. (2002) Postsecondary education descriptive analysis reports (NCES 2003- 154). U.S. Department of Education, National Center for Education Statistics, Washington, USA.

    Google Scholar 

  • Skinner, E. A., Zimmer-Gembeck, M. J., Connell, J. P., Eccles, J. S., & Wellborn, J. G. (1998). Individual differences and the development of perceived control. Monographs of the Society for Research in Child Development, i-231.

  • So, H. J., & Brush, T. A. (2008). Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: Relationships and critical factors. Computers & Education, 51(1), 318–336.

    Article  Google Scholar 

  • Strauss, A., & Corbin, J. (1994). Grounded theory methodology. Handbook of Qualitative Research, 17, 273–285.

    Google Scholar 

  • Terenzini, P. T., Yaeger, P. M., Bohr, L., Pascarella, E. T., & Amaury, N. (1997). African American College Students' Experiences in HBCUs and PWIs and Learning Outcomes.

  • Trninic, D., Swanson, H., & Kapur, M. (2018). Productive dissent in learning communities. Instructional Science, 46(4), 621–625.

    Article  Google Scholar 

  • Vargas-Madriz, L. F., Nocente, N. (2016). Experiences of Blending - Elementary Calculus for Physical Sciences: A Summary of Student Surveys & Student and Instructor Interviews. University of Alberta, Centre for Teaching and Learning.

    Google Scholar 

  • Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.

  • Vygotsky, L. S. (1981). The genesis of higher mental functions. In J.V. Wertsch (ed.) The Concept of Activity in Soviet Psychology. Armonk, NY: M.E. Sharpe (pp.144−188).

  • Wieman, C. (2007). Why not try a scientific approach to science education? Change: The Magazine of Higher Learning 39(5), 9–15.

  • Wu, J. H., Tennyson, R. D., & Hsia, T. L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & Education, 55(1), 155–164.

  • Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary educational psychology, 25(1), 68–81.

Download references

Acknowledgements

We thank Norma Nocente and Francisco Vargas L. M. of the Centre for Teaching and Learning at the University of Alberta for their work in collecting the original data set and for sharing their work for our analysis.

Funding

The research was supported by four teaching awards from The Centre for Teaching and Learning at the University of Alberta. The awards were used to fund the conversion of courses into the blended learning formats analysed here.

Author information

Authors and Affiliations

  1. Department of Physics, University of Alberta, Edmonton, AB, T6G 2R3, Canada

    Stephen Lane

  2. Faculty of Science, University of Alberta, Edmonton, AB, T6G 2R3, Canada

    John G. Hoang & Anna Rissanen

  3. Department of Educational Psychology, University of Alberta, Edmonton, AB, T6G 2R3, Canada

    Jacqueline P. Leighton

Authors
  1. Stephen Lane
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John G. Hoang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jacqueline P. Leighton
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anna Rissanen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stephen Lane.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lane, S., Hoang, J.G., Leighton, J.P. et al. Engagement and Satisfaction: Mixed-Method Analysis of Blended Learning in the Sciences. Can. J. Sci. Math. Techn. Educ. 21, 100–122 (2021). https://doi.org/10.1007/s42330-021-00139-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42330-021-00139-5

Keywords

  • Blended learning
  • Science education
  • Satisfaction
  • Emotional engagement
  • Cognitive engagement
  • Behavioural engagement